Use case

Cross-system reconciliation: the invisible work that drains the most operations hours

Cross-system reconciliation is the daily work of comparing the same record across two or more systems (carrier portal, OMS, ERP, core banking, MES) and flagging the differences. It is invisible because no one is paid to do it as a named role: a planner stitches Maersk, Descartes and NetSuite by eye before coffee. It is the safest first agent target because it is **read-only by default**, high-volume, low-judgement, and the constraint is usually an auditor rather than a customer.

What we touch

The reconciliation workflows we automate first

01

Shipment status reconciliation across Maersk or MSC carrier portals, the Descartes customs broker file and NetSuite or SAP OMS

02

Three-way invoice match in SAP S/4HANA Ariba against the PO line and the warehouse goods-receipt note

03

Regulatory report assembly across Murex or Calypso, the risk engine and the State Street custodian feed

04

Production schedule reconciliation across SAP S/4HANA, the Rockwell MES and the LIMS quality file

05

Supplier scorecard updates joining Coupa, the SAP quality module and Oracle Fusion finance

06

Customer master deduplication across Salesforce, Zuora billing and the SAP customer master

07

Inventory position reconciliation across Manhattan WMS, the NetSuite finance ledger and the Shopify storefront stock feed

08

Service-desk ticket status reconciliation across ServiceNow ITSM, Datadog monitoring and the PagerDuty on-call rota

09

Trade settlement reconciliation across Bloomberg AIM, the BNY Mellon custodian feed and the Oracle general ledger

Typical impact

What teams typically see when the agent goes live

Our planner at 8:14am spends three to four hours of her eight-hour shift on that same Maersk-Descartes-NetSuite comparison. At a fully loaded planner cost of around 36,000 to 52,000 US dollars per year of recovered time, a ten-person planning desk recovers 360,000 to 520,000 dollars annually once the agent handles the first pass. The agent itself runs at roughly 3 to 12 dollars per day in API costs, depending on volume. The same arithmetic plays out in AP, where a six-clerk three-way match desk against SAP S/4HANA Ariba is the easiest single payback case we see, and in bank back-office, where regulatory reporting eats the most senior analyst hours in the building.

These are industry-typical ranges from published studies and benchmarks, not specific Synarsi-client outcomes.

How an engagement works

From first call to live agent

  1. 01
    Scope. Pick the single reconciliation workflow that cost your team the most hours last quarter. Name the systems by product, not category, because the API surface of SAP S/4HANA is nothing like JD Edwards, and Maersk's carrier portal behaves nothing like MSC's. Name the binding constraint: external audit, FCA or SEC deadline, customer SLA, or the month-end close calendar. The constraint sets the latency budget for the agent. Then list the exception types your operators already recognise: missing record, mismatched quantity, mismatched date, mismatched counterparty, mismatched currency. That list is the spine of the agent's output and it almost always already exists as a shared Google Sheet or a corner of someone's OneDrive.
  2. 02
    Integrate. Confirm API or feed access to every system before any agent design work begins. This is where projects die quietly. Half the systems will have a clean REST API, a quarter will need an SFTP file drop, and a quarter will need RPA or a vendor-supplied extract from a portal that has not been touched since 2014. Design the normalisation layer next: every record from every source maps to a canonical schema with a stable join key. Define the exceptions taxonomy formally and version it. The agent tags every flagged record with one of those exception types, and your operators will trust the output only when the vocabulary matches what they already use in the morning standup.
  3. 03
    Shadow. Run the agent read-only against live data for two to four weeks before it writes anything anywhere. Compare its exception list against what your operators flag manually over the same window. Calibrate the thresholds: what counts as a meaningful date mismatch, how much currency drift is rounding versus a real break, when a missing record becomes urgent. Build the operator vocabulary in this phase too. The labels the agent uses in its dashboard need to be the labels your team uses out loud. Shadow mode is also where you discover the systems that are slower or flakier than the procurement contract promised.
  4. 04
    Cut over. Stand up a single source of truth dashboard with the agent's reconciliation result as the master view. Operators stop opening the four source systems for the routine 90 per cent and only open them for the exceptions the agent escalates. Hold a weekly drift review for the first quarter. The agent's exception distribution will shift as upstream systems change, and the taxonomy needs to evolve with it. Define the kill switch and the rollback path explicitly. The cut-over is also the point where leadership finally sees the work, because the dashboard makes the previously invisible reconciliation effort legible for the first time. Read more on how we sequence this in our [methodology](/methodology/).

Recognise this in your team?

Tell us about the reconciliation workflow that costs your team the most hours. We will reply within one business day with a useful first answer.

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